Statistical Figures of Merit for the Feature Selective Validation Method
This paper presents point-by-point Feature Selective Validation (FSV) data as a continuous distribution function, rather than in the more usual confidence histogram form, and from that derives the mean, standard deviation, skewness and kurtosis. The increased information that this offers is shown by presenting again the data from three previous exercises to verify FSV performance against visual assessment but including the standard deviation, where it is demonstrated that more robust conclusions about FSV overall assessment can be provided. The implication of the use of statistical data within FSV for including uncertainty in data comparisons is discussed.
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
Citation : Zhang, G., Duffy, A. and Orlandi, A. (2017) Statistical Figures of Merit for the Feature Selective Validation Method; IEEE Transactions on EMC, 59 (5), pp. 1482-1489
Research Group : Engineering and Physical Sciences Institute (EPsi)
Research Institute : Institute of Engineering Sciences (IES)
Peer Reviewed : Yes